Bi-criteria optimization model for a four stage centralized supply chain
Open Access
- Author:
- Vijayaragavan, Koushiik
- Graduate Program:
- Industrial Engineering
- Degree:
- Master of Science
- Document Type:
- Master Thesis
- Date of Defense:
- None
- Committee Members:
- Arunachalam Ravindran, Thesis Advisor/Co-Advisor
- Keywords:
- supply chain
Multi-criteria optimization
goal programming - Abstract:
- The aim of this thesis is to develop a multi-criteria multi-period linear integer programming model and solution methods for a centralized four-stage supply chain. In most supply chain optimization models, the decisions on transportation and inventory have traditionally been considered as separate entities to avoid complex mathematical formulations. This thesis incorporates the transportation and inventory decisions in the same model. The model helps in identifying the optimal modes of transport to be used between each stage of the supply chain, the optimal inventory levels to be maintained at each stage thereby minimizing the overall cost incurred in the supply chain. While minimizing the overall supply chain cost, the responsiveness of the supply chain is also maximized by modeling it as a bi-criteria optimization problem. In the proposed model, multiple modes of transport are used between the different stages of the supply chain with an incremental quantity discount cost structure for the freight rates. For inventory, there is a company owned warehouse with a finite storage capacity and a leased warehouse with infinite capacity if the capacity at the company owned warehouse is exceeded. The leased warehouse has an incremental quantity discount cost structure for the storage space. There is only one product flowing in the supply chain. The multi-criteria optimization model is solved using non preemptive goal programming by giving weights to the two objectives and also by preemptive goal programming assigning different priorities to the objectives. The model identifies the right amount of quantity to be shipped by the appropriate mode of transport at each supply chain stage, the right amount of inventory to be stored at the warehouses (company owned and leased) and the accumulated backorder at the various stages (if any) in order to minimize the total supply chain cost and maximize the customer responsiveness. The model is illustrated with simulated data for two scenarios, one for prioritizing the cost over the customer responsiveness and another for prioritizing customer responsiveness over cost. The two scenarios are compared based on the shipping pattern, inventory storage and the number of backorders.